How U-M engineers and clinicians are unlocking AI’s healthcare potential
‘Practicing medicine is hard and it feels like it’s getting harder. AI can help clinicians deliver really high quality care’.
At the University of Michigan, engineers and clinicians have collaborated for more than a decade to translate AI research into tools that support medical staff and patients alike.
In a Q&A, longtime collaborators computer scientist Jenna Wiens and critical care physician Mike Sjoding discuss how AI could transform healthcare, what that looks like exactly, and why doctors and engineers need to work together to advance this shift. They also discuss some of the ways AI is being used at Michigan Medicine as well as their own projects.
“Practicing medicine is hard and it feels like it’s getting harder,” Sjoding said. “We’re awash in all this data. Also the pace of medical discovery is shockingly fast now. It’s hard for folks to keep up. So I think of AI as systems that can help clinicians deliver really high quality care amid these challenges.”
Specific questions discussed include:
- What is AI in this context? What sorts of AI is being integrated into medicine?
- How could AI revolutionize healthcare?
- How do clinicians and engineers collaborate on AI at Michigan, and why is it so important that they’re both involved?
- What are some ways AI is being used at Michigan Medicine?
They explain that much of today’s healthcare AI is powered by machine learning—systems designed to make sense of enormous volumes of clinical data that clinicians cannot realistically review on their own. These tools can predict risk, analyze medical images, summarize records and reduce documentation workload.
“Our work goes beyond developing the model,” Wiens said. “We need to determine how to ensure that clinicians use it in an optimal way. It’s a human-AI collaboration. But it’s ultimately the clinician that’s making the diagnostic decision.”
Wiens is an associate professor of computer science and engineering and co-director of U-M’s AI & Digital Health Innovation (AI&DHI). Sjoding is an associate professor of internal medicine at the U-M Medical School.
AI contributed to this human-edited summary of the article AI in healthcare: How engineers and clinicians at U-M are unlocking its potential together by Nicole Casal Moore.